Observer Design for (max,+) Linear Systems

This paper deals with control of max-plus linear systems which are discrete event dynamic systems characterized by delays and synchronization phenomena. Control of these discrete event systems consists in choosing the date of input events in order to reach some performances, e.g., to obtain output events at the given dates. This kind of control is optimal according to a just-in-time criterion when the input events dates are delayed as much as possible while ensuring the output events occur before the given output events dates. This paper presents an observed-based controller, where only a subset of the states obtained from measurement is available for the controller. This is an output feedback problem which is solved in two steps, first an observer yields an estimation of the state by using the input and the output measurements, then this estimated state is used in state feedback scheme. The observer and state feedback design is based on the residuation theory which is suitable to deal with mapping inversion defined over order sets

Adaptive State Observation of Linear Time-Varying Systems with Delayed Measurements and Unknown Parameters

International audienceIn this paper we address the problem of adaptive state observation of linear timevarying systems with delayed measurements and unknown parameters. Our new developments extend the results reported in 1 and 2. The case with known parameters has been studied by many researchers-see 3,4 and references therein. We show in this paper that the generalized parameter estimation-based observer design proposed in 5 provides a very simple solution for the unknown parameter case. Moreover, when this observer design technique is combined with the dynamic regressor extension and mixing estimation procedure 6,7 , the estimated state and parameters converge in fixed-time imposing extremely weak excitation assumptions

On general systems with network-enhanced complexities

In recent years, the study of networked control systems (NCSs) has gradually become an active research area due to the advantages of using networked media in many aspects such as the ease of maintenance and installation, the large flexibility and the low cost. It is well known that the devices in networks are mutually connected via communication cables that are of limited capacity. Therefore, some network-induced phenomena have inevitably emerged in the areas of signal processing and control engineering. These phenomena include, but are not limited to, network-induced communication delays, missing data, signal quantization, saturations, and channel fading. It is of great importance to understand how these phenomena influence the closed-loop stability and performance properties

Nonlinear predictors for systems with bounded trajectories and delayed measurements

Novel nonlinear predictors are studied for nonlinear systems with delayed measurements without assuming globally Lipschitz conditions or a known predictor map but requiring instead bounded state trajectories. The delay is constant and known. These nonlinear predictors consists of a series of dynamic filters that generate estimates of the state vector (and its maximum magnitude) at different delayed time instants which differ from one another by a small fraction of the overall delay

Recent advances on recursive filtering and sliding mode design for networked nonlinear stochastic systems: A survey

Copyright © 2013 Jun Hu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Some recent advances on the recursive filtering and sliding mode design problems for nonlinear stochastic systems with network-induced phenomena are surveyed. The network-induced phenomena under consideration mainly include missing measurements, fading measurements, signal quantization, probabilistic sensor delays, sensor saturations, randomly occurring nonlinearities, and randomly occurring uncertainties. With respect to these network-induced phenomena, the developments on filtering and sliding mode design problems are systematically reviewed. In particular, concerning the network-induced phenomena, some recent results on the recursive filtering for time-varying nonlinear stochastic systems and sliding mode design for time-invariant nonlinear stochastic systems are given, respectively. Finally, conclusions are proposed and some potential future research works are pointed out.This work was supported in part by the National Natural Science Foundation of China under Grant nos. 61134009, 61329301, 61333012, 61374127 and 11301118, the Engineering and Physical Sciences Research Council (EPSRC) of the UK under Grant no. GR/S27658/01, the Royal Society of the UK, and the Alexander von Humboldt Foundation of Germany

Robust control tools for traffic monitoring in TCP/AQM networks

Several studies have considered control theory tools for traffic control in communication networks, as for example the congestion control issue in IP (Internet Protocol) routers. In this paper, we propose to design a linear observer for time-delay systems to address the traffic monitoring issue in TCP/AQM (Transmission Control Protocol/Active Queue Management) networks. Due to several propagation delays and the queueing delay, the set TCP/AQM is modeled as a multiple delayed system of a particular form. Hence, appropriate robust control tools as quadratic separation are adopted to construct a delay dependent observer for TCP flows estimation. Note that, the developed mechanism enables also the anomaly detection issue for a class of DoS (Denial of Service) attacks. At last, simulations via the network simulator NS-2 and an emulation experiment validate the proposed methodology